RETRACTED: Music genre selection based on computer data analysis for user preference using fuzzy classification by deep learning model.

The article focuses on music genre classification based on user preferences using a combination of feature selection and advanced machine learning models, specifically the Convolutional Belief Transfer Gaussian model (CBTG) and Fuzzy Recurrent Adversarial Encoder Neural Network (FRAENN). It addresses challenges in music information retrieval (MIR) by transforming audio signals into uniform representations and applying deep learning techniques to large datasets such as GTZAN and Free Music Archive (FMA). Experimental results demonstrate that the proposed models outperform traditional methods like CNN and LDA in accuracy, precision, and F1 score while reducing processing time by using a subset of features. The study highlights the complexity of music genre classification and the importance of efficient, user-preference-based recommendation systems in the digital music streaming industry.